On Liu's simplicial depth and Randles' interdirections

DOI10.1016/j.csda.2016.02.002zbMath1468.62177OpenAlexW2286011825MaRDI QIDQ1659197

Yunfei Wang, Robert J. Serfling

Publication date: 15 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2016.02.002

zbMATH Keywords

simplicial depthmultivariatesign testscomputational burdeninterdirections

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric hypothesis testing (62G10) Hypothesis testing in multivariate analysis (62H15) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items

Affine invariant depth-based tests for the multivariate one-sample location problem

Uses Software

• AS 307

Cites Work

• Limit theorems for \(U\)-processes
• Affine-invariant aligned rank tests for the multivariate general linear model with VARMA errors
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• The number of triangles covering the center of an \(n\)-set
• Limit theorems for the simplicial depth
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• Lower bounds for computing statistical depth.
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• General notions of statistical depth function.
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• Optimal procedures based on interdirections and pseudo-Mahalanobis ranks for testing multivariate elliptic white noise against ARMA dependence
• On the performance of some robust nonparametric location measures relative to a general notion of multivariate symmetry
• Equivariance and invariance properties of multivariate quantile and related functions, and the role of standardisation
• A New Bivariate Sign Test
• A multivariate signed sum test for theone-sample location problem
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• A Multivariate Signed-Rank Test for the One-Sample Location Problem
• On a notion of simplicial depth
• Bivariate Sign Tests
• Sign Tests in Multidimension: Inference Based on the Geometry of the Data Cloud
• Algorithm AS 307: Bivariate Location Depth
• A Simpler, Affine-Invariant, Multivariate, Distribution-Free Sign Test
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